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Computing Up – Theories of theories of everything
Inspired by a WIRED profile of Karl Friston, Michael Littman and Dave Ackley talk about theories of everything, and theories thereof.
Computing Up
Conversations about computation writ large, with Michael Littman and Dave Ackley.
Computing Up
Conversations about computation writ large, with Michael Littman and Dave Ackley.
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monthly digest
AIhub monthly digest: May 2026 – AI for science, the lottery ticket hypothesis, and world models
Lucy Smith
28 May 2026
Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.
You probably wouldn’t notice if an AI chatbot slipped ads into its responses
The Conversation
27 May 2026
Research suggests AI chatbots could easily be used for covert advertising to manipulate their human users.
The Good Robot podcast: the future of data centres and digital sovereignty with Friederike von Franqué
The Good Robot Podcast
26 May 2026
Can cloud infrastructure be owned and governed by the people, and not just Big Tech?
coffee corner
AIhub coffee corner: World models
AIhub
22 May 2026
The AIhub coffee corner captures the musings of AI experts over a short conversation.
Why the world’s banks are so worried about Anthropic’s latest AI model
The Conversation
21 May 2026
The finance world’s concern rests on the impressive cyber capabilities of a product called Mythos.
Embracing empiricism – from the lottery hypothesis to creating real-world impact: an interview with Jonathan Frankle
Ella Scallan
20 May 2026
Jonathan Frankle discusses empiricism, making an impact, and the legacy of his lottery ticket hypothesis.
A faster way to estimate AI power consumption
MIT News
19 May 2026
The “EnergAIzer” method generates reliable results in seconds, enabling data center operators to efficiently allocate resources and reduce wasted energy.
Introducing ARFBench: A time series question-answering benchmark based on real incidents
ML@CMU
18 May 2026
To resolve system failures, engineers must troubleshoot outages quickly.
